Journal article
Minimum Detectable Differences in Electrocochleography Measurements: Bayesian-Based Predictions
Journal of the Association for Research in Otolaryngology, Vol.24(2), pp.217-237
04/2023
DOI: 10.1007/s10162-023-00888-0
PMCID: PMC10121985
PMID: 36795197
Abstract
Physiology of the cochlea and auditory nerve can be assessed with electrocochleography (ECochG), a technique that involves measuring auditory evoked potentials from an electrode placed near or within the cochlea. Research, clinical, and operating room applications of ECochG have in part centered on measuring the auditory nerve compound action potential (AP) amplitude, the summating potential (SP) amplitude, and the ratio of the two (SP/AP). Despite the common use of ECochG, the variability of repeated amplitude measurements for individuals and groups is not well understood. We analyzed ECochG measurements made with a tympanic membrane electrode in a group of younger normal-hearing participants to characterize the within-participant and group-level variability for the AP amplitude, SP amplitude, and SP/AP amplitude ratio. Results show that the measurements have substantial variability and that, especially with smaller sample sizes, significant reduction in variability can be obtained by averaging measurements across repeated electrode placements within subjects. Using a Bayesian-based model of the data, we generated simulated data to predict minimum detectable differences in AP and SP amplitudes for experiments with a given number of participants and repeated measurements. Our findings provide evidence-based recommendations for the design and sample size determination of future experiments using ECochG amplitude measurements, and the evaluation of previous publications in terms of sensitivity to detecting experimental effects on ECochG amplitude measurements. Accounting for the variability of ECochG measurements should result in more consistent results in the clinical and basic assessments of hearing and hearing loss, either hidden or overt.
Details
- Title: Subtitle
- Minimum Detectable Differences in Electrocochleography Measurements: Bayesian-Based Predictions
- Creators
- Shawn S Goodman - University of IowaJeffery T Lichtenhan - University of South FloridaSkyler G Jennings - University of Utah
- Resource Type
- Journal article
- Publication Details
- Journal of the Association for Research in Otolaryngology, Vol.24(2), pp.217-237
- DOI
- 10.1007/s10162-023-00888-0
- PMID
- 36795197
- PMCID
- PMC10121985
- eISSN
- 1438-7573
- Grant note
- K23 DC014752 / NIDCD NIH HHS
- Language
- English
- Electronic publication date
- 02/16/2023
- Date published
- 04/2023
- Academic Unit
- Communication Sciences and Disorders
- Record Identifier
- 9984368160002771
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